Simulating Intestinal Transporter and Enzyme Activity in a Physiologically Based Pharmacokinetic Model for Tenofovir Disoproxil Fumarate

ABSTRACT Tenofovir disoproxil fumarate (TDF), a prodrug of tenofovir, has oral bioavailability (25%) limited by intestinal transport (P-glycoprotein), and intestinal degradation (carboxylesterase). However, the influence of luminal pancreatic enzymes is not fully understood. Physiologically based pharmacokinetic (PBPK) modeling has utility for estimating drug exposure from in vitro data. This study aimed to develop a PBPK model that included luminal enzyme activity to inform dose reduction strategies. TDF and tenofovir stability in porcine pancrelipase concentrations was assessed (0, 0.48, 4.8, 48, and 480 U/ml of lipase; 1 mM TDF; 37°C; 0 to 30 min). Samples were analyzed using mass spectrometry. TDF stability and permeation data allowed calculation of absorption rates within a human PBPK model to predict plasma exposure following 6 days of once-daily dosing with 300 mg of TDF. Regional absorption of drug was simulated across gut segments. TDF was degraded by pancrelipase (half-lives of 0.07 and 0.62 h using 480 and 48 U/ml, respectively). Previously reported maximum concentration (C max; 335 ng/ml), time to C max (T max; 2.4 h), area under the concentration-time curve from 0 to 24 h (AUC0–24; 3,045 ng · h/ml), and concentration at 24 h (C 24; 48.3 ng/ml) were all within a 0.5-fold difference from the simulated C max (238 ng/ml), T max (3 h), AUC0–24 (3,036 ng · h/ml), and C 24 (42.7 ng/ml). Simulated TDF absorption was higher in duodenum and jejunum than in ileum (p<0.05). These data support that TDF absorption is limited by the action of intestinal lipases. Our results suggest that bioavailability may be improved by protection of drug from intestinal transporters and enzymes, for example, by coadministration of enzyme-inhibiting agents or nanoformulation strategies.

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Development of a Physiologically Based Pharmacokinetic Model for Prediction of Ethanol Concentration-Time Profile in Different Organs

Alcohol and Alcoholism ◽

10.1093/alcalc/agaa129 ◽

2020 ◽

Author(s):

Armin Sadighi ◽

Lorenzo Leggio ◽

Fatemeh Akhlaghi

Keyword(s):

Pbpk Model ◽

Organ Damage ◽

Time Profile ◽

Sensitivity Analyses ◽

Pbpk Modeling ◽

Time Curve ◽

Physiologically Based Pharmacokinetic ◽

Concentration Time ◽

Physiologically Based

Abstract Aims A physiologically based pharmacokinetic (PBPK) modeling approach was used to simulate the concentration-time profile of ethanol (EtOH) in stomach, duodenum, plasma and other tissues upon consumption of beer and whiskey under fasted and fed conditions. Methods A full PBPK model was developed for EtOH using the advanced dissolution, absorption and metabolism (ADAM) model fully integrated into the Simcyp Simulator® 15 (Simcyp Ltd., Sheffield, UK). The prediction performance of the developed model was verified and the EtOH concentration-time profile in different organs was predicted. Results Simcyp simulation showed ≤ 2-fold difference in values of EtOH area under the concentration-time curve (AUC) in stomach and duodenum as compared to the observed values. Moreover, the simulated EtOH maximum concentration (Cmax), time to reach Cmax (Tmax) and AUC in plasma were comparable to the observed values. We showed that liver is exposed to the highest EtOH concentration, faster than other organs (Cmax = 839.50 mg/L and Tmax = 0.53 h), while brain exposure of EtOH (AUC = 1139.43 mg·h/L) is the highest among all other organs. Sensitivity analyses (SAs) showed direct proportion of EtOH rate and extent of absorption with administered EtOH dose and inverse relationship with gastric emptying time (GE) and steady-state volume of distribution (Vss). Conclusions The current PBPK model approach might help with designing in vitro experiments in the area of alcohol organ damage or alcohol-drug interaction studies.

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Development of Physiologically Based Pharmacokinetic Model for Orally Administered Fexuprazan in Humans

Pharmaceutics ◽

10.3390/pharmaceutics13060813 ◽

2021 ◽

Vol 13 (6) ◽

pp. 813

Author(s):

Yoo-Seong Jeong ◽

Min-Soo Kim ◽

Nora Lee ◽

Areum Lee ◽

Yoon-Jee Chae ◽

...

Keyword(s):

Gastric Acid ◽

Pbpk Model ◽

Pbpk Modeling ◽

Drug Candidate ◽

Metabolite Formation ◽

Pbpk Models ◽

Physiologically Based Pharmacokinetic ◽

Physiologically Based

Fexuprazan is a new drug candidate in the potassium-competitive acid blocker (P-CAB) family. As proton pump inhibitors (PPIs), P-CABs inhibit gastric acid secretion and can be used to treat gastric acid-related disorders such as gastroesophageal reflux disease (GERD). Physiologically based pharmacokinetic (PBPK) models predict drug interactions as pharmacokinetic profiles in biological matrices can be mechanistically simulated. Here, we propose an optimized and validated PBPK model for fexuprazan by integrating in vitro, in vivo, and in silico data. The extent of fexuprazan tissue distribution in humans was predicted using tissue-to-plasma partition coefficients in rats and the allometric relationships of fexuprazan distribution volumes (VSS) among preclinical species. Urinary fexuprazan excretion was minimal (0.29–2.02%), and this drug was eliminated primarily by the liver and metabolite formation. The fraction absorbed (Fa) of 0.761, estimated from the PBPK modeling, was consistent with the physicochemical properties of fexuprazan, including its in vitro solubility and permeability. The predicted oral bioavailability of fexuprazan (38.4–38.6%) was within the range of the preclinical datasets. The Cmax, AUClast, and time-concentration profiles predicted by the PBPK model established by the learning set were accurately predicted for the validation sets.

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1315. No Dose Adjustment of Metformin with Fostemsavir Coadministration Based on Mechanistic Static and Physiologically Based Pharmacokinetic Models

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.1497 ◽

2020 ◽

Vol 7 (Supplement_1) ◽

pp. S669-S669

Author(s):

Dung N Nguyen ◽

Xiusheng Miao ◽

Mindy Magee ◽

Guoying Tai ◽

Peter D Gorycki ◽

...

Keyword(s):

Dose Adjustment ◽

Pbpk Model ◽

Systemic Exposure ◽

Multidrug Resistant ◽

Pbpk Modeling ◽

Repeat Dose ◽

Physiologically Based Pharmacokinetic ◽

Physiologically Based

Abstract Background Fostemsavir (FTR) is an oral prodrug of the first-in-class attachment inhibitor temsavir (TMR) which is being evaluated in patients with multidrug resistant HIV-1 infection. In vitro studies indicated that TMR and its 2 major metabolites are inhibitors of organic cation transporters (OCT)1, OCT2, and multidrug and toxin extrusion transporters (MATEs). To assess the clinical relevance, of OCT and MATE inhibition, mechanistic static DDI prediction with calculated Imax,u/IC50 ratios was below the cut-off limits for a DDI flag based on FDA guidelines and above the cut-off limits for MATEs based on EMA guidelines. Methods Metformin is a commonly used probe substrate for OCT1, OCT2 and MATEs. To predict the potential for a drug interaction between TMR and metformin, a physiologically based pharmacokinetic (PBPK) model for TMR was developed based on its physicochemical properties, in vitro and in vivo data. The model was verified and validated through comparison with clinical data. The TMR PBPK model accurately described AUC and Cmax within 30% of the observed data for single and repeat dose studies with or without food. The SimCYP models for metformin and ritonavir were qualified using literature data before applications of DDI prediction for TMR Results TMR was simulated at steady state concentrations after repeated oral doses of FTR 600 mg twice daily which allowed assessment of the potential OCT1, OCT2, and MATEs inhibition by TMR and metabolites. No significant increase in metformin systemic exposure (AUC or Cmax) was predicted with FTR co-administration. In addition, a sensitivity analysis was conducted for either hepatic OCT1 Ki, or renal OCT2 and MATEs Ki values. The model output indicated that, a 10-fold more potent Ki value for TMR would be required to have a ~15% increase in metformin exposure Conclusion Based on mechanistic static models and PBPK modeling and simulation, the OCT1/2 and MATEs inhibition potential of TMR and its metabolites on metformin pharmacokinetics is not clinically significant. No dose adjustment of metformin is necessary when co-administered with FTR Disclosures Xiusheng Miao, PhD, GlaxoSmithKline (Employee) Mindy Magee, Doctor of Pharmacy, GlaxoSmithKline (Employee, Shareholder) Peter D. Gorycki, BEChe, MSc, PhD, GSK (Employee, Shareholder) Katy P. Moore, PharmD, RPh, ViiV Healthcare (Employee)

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Application of physiologically based pharmacokinetic modeling for sertraline dosing recommendations in pregnancy

npj Systems Biology and Applications ◽

10.1038/s41540-020-00157-3 ◽

2020 ◽

Vol 6 (1) ◽

Author(s):

Blessy George ◽

Annie Lumen ◽

Christine Nguyen ◽

Barbara Wesley ◽

Jian Wang ◽

...

Keyword(s):

Pregnant Women ◽

Gestational Age ◽

Drug Exposure ◽

Pbpk Model ◽

Pbpk Modeling ◽

Quantitative Prediction ◽

Pharmacokinetic Parameters ◽

Physiologically Based Pharmacokinetic ◽

Physiologically Based ◽

In Pregnancy

Abstract Pregnancy is a period of significant change that impacts physiological and metabolic status leading to alterations in the disposition of drugs. Uncertainty in drug dosing in pregnancy can lead to suboptimal therapy, which can contribute to disease exacerbation. A few studies show there are increased dosing requirements for antidepressants in late pregnancy; however, the quantitative data to guide dose adjustments are sparse. We aimed to develop a physiologically based pharmacokinetic (PBPK) model that allows gestational-age dependent prediction of sertraline dosing in pregnancy. A minimal physiological model with defined gut, liver, plasma, and lumped placental-fetal compartments was constructed using the ordinary differential equation solver package, ‘mrgsolve’, in R. We extracted data from the literature to parameterize the model, including sertraline physicochemical properties, in vitro metabolism studies, disposition in nonpregnant women, and physiological changes during pregnancy. The model predicted the pharmacokinetic parameters from a clinical study with eight subjects for the second trimester and six subjects for the third trimester. Based on the model, gestational-dependent changes in physiology and metabolism account for increased clearance of sertraline (up to 143% at 40 weeks gestational age), potentially leading to under-dosing of pregnant women when nonpregnancy doses are used. The PBPK model was converted to a prototype web-based interactive dosing tool to demonstrate how the output of a PBPK model may translate into optimal sertraline dosing in pregnancy. Quantitative prediction of drug exposure using PBPK modeling in pregnancy will support clinically appropriate dosing and increase the therapeutic benefit for pregnant women.

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Physiologically Based Pharmacokinetic Modeling of Salivary Concentrations for Noninvasive Biomonitoring of 2,4-Dichlorophenoxyacetic Acid (2,4-D)

Toxicological Sciences ◽

10.1093/toxsci/kfz206 ◽

2019 ◽

Vol 172 (2) ◽

pp. 330-343

Author(s):

Alice A Han ◽

Charles Timchalk ◽

Zana A Carver ◽

Thomas J Weber ◽

Kimberly J Tyrrell ◽

...

Keyword(s):

Pbpk Model ◽

Pbpk Modeling ◽

Dichlorophenoxyacetic Acid ◽

Diffusion Limited ◽

Physiologically Based Pharmacokinetic ◽

Physiologically Based ◽

Dynamic Time ◽

2,4 Dichlorophenoxyacetic Acid

Abstract Saliva has become a favorable sample matrix for biomonitoring due to its noninvasive attributes and overall flexibility in collection. To ensure measured salivary concentrations reflect the exposure, a solid understanding of the salivary transport mechanism and relationships between salivary concentrations and other monitored matrices (ie, blood, urine) is needed. Salivary transport of a commonly applied herbicide, 2,4-dichlorophenoxyacetic acid (2,4-D), was observed in vitro and in vivo and a physiologically based pharmacokinetic (PBPK) model was developed to translate observations from the cell culture model to those in animal models and further evaluate 2,4-D kinetics in humans. Although apparent differences in experimental in vitro and in vivo saliva:plasma ratios (0.034 and 0.0079) were observed, simulations with the PBPK model demonstrated dynamic time and dose-dependent saliva:plasma ratios, elucidating key mechanisms affecting salivary transport. The model suggested that 2,4-D exhibited diffusion-limited transport to saliva and was additionally impacted by protein binding saturation and permeability across the salivary gland. Consideration of sampling times post-exposure and potential saturation of transport mechanisms are then critical aspects for interpreting salivary 2,4-D biomonitoring observations. This work utilized PBPK modeling in in vitro to in vivo translation to explore benefits and limitations of salivary analysis for occupational biomonitoring.

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P01 Application of feto-placental-maternal physiologically-based pharmacokinetic model to predict tenofovir concentration during pregnancy

Archives of Disease in Childhood ◽

10.1136/archdischild-2019-esdppp.40 ◽

2019 ◽

Vol 104 (6) ◽

pp. e17.2-e18

Author(s):

K Abduljalil ◽

TN Johnson ◽

M Jamei

Keyword(s):

Tenofovir Disoproxil Fumarate ◽

Drug Exposure ◽

Pbpk Model ◽

Model Parameters ◽

List Type ◽

Large Variability ◽

Pbpk Models ◽

Physiologically Based Pharmacokinetic ◽

Physiologically Based ◽

Fetal Organs

BackgroundTenofovir is a drug used in combination with other anti-HIV drugs to treat patients with HIV-1 infection. It is used during pregnancy to reduce the risk of HIV transmission to the child. The aim of this work is to use a Physiologically-Based Pharmacokinetic (PBPK) model for prediction of maternal and fetal tenofovir concentration at birth.MethodsA full Feto-Placental-Maternal PBPK model that includes placenta as a 3-comparment permeability limited organ and 14 compartments for different fetal organs was developed using physiological1,2 and drug specific parameters3 to predict tenofovir concentration in 50 virtual pregnant mothers at term after single administration of 600 mg of tenofovir disoproxil fumarate (272 mg tenofovir). The mechanistic model implemented using the Simcyp Lua interface within the Simcyp Simulator. Fetal as well as maternal tissue to plasma ratio values were predicted using the Rodgers & Rowland method with a scalar of 1.5. Predictions of tenofovir maternal and fetal plasma concentration were compared to reported observations.4ResultsIn spite of the large variability in the observed data, the model adequately replicated the maternal as well as fetal clinical observations.4 The placenta transfer by cotyledon was changed 10 times the mean reported value from perfusion experiment.5 All other model parameters were calculated using bottom-up approach.The maternal predicted-to-observed ratio for AUC24hr and Cmax was 1.13 and 1.08, respectively. The predicted fetal exposure was well predicted within the 5th and 95th percentiles and was 0.51 of maternal exposure (AUC24h), the reported value is 0.60.4ConclusionThe developed feto-placental-maternal PBPK models can be used to predict drug exposure in fetal organs during in utero growth. The inter-subject variability can be predicted incorporating both the drug physicochemical properties and system (placental, maternal and fetal) parameters.ReferencesAbduljalil, et al. Clin Pharmacokinet 2018;57(9):1149–1171.Abduljalil, et al. Clin Pharmacokinet 2019;58:235–262Gilead Sciences, Inc. Product Information: tenofovir disoproxil fumarate (VIREAD) tablets.Hirt D, et al., Clin Pharmacol Ther 2009; 85: 182–9.De Sousa Mendes, et al., Br J Clin Pharmacol 2016;81(4):646–57.Disclosure(s)Nothing to disclose

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Drug-drug interaction (DDI) assessments of ruxolitinib, a dual substrate of CYP3A4 and CYP2C9, using a verified physiologically based pharmacokinetic (PBPK) model to support regulatory submissions

Drug Metabolism and Personalized Therapy ◽

10.1515/dmpt-2018-0042 ◽

2019 ◽

Vol 34 (2) ◽

Cited By ~ 1

Author(s):

Kenichi Umehara ◽

Felix Huth ◽

Yi Jin ◽

Hilmar Schiller ◽

Vassilios Aslanis ◽

...

Keyword(s):

Dose Reduction ◽

Dose Adjustment ◽

Pbpk Model ◽

Pbpk Modeling ◽

Cyp Enzymes ◽

Physiologically Based Pharmacokinetic ◽

Physiologically Based ◽

Cyp3a4 Inhibitors ◽

Simulation Results

Abstract Ruxolitinib is mainly metabolized by cytochrome P450 (CYP) enzymes CYP3A4 and CYP2C9 followed by minor contributions of other hepatic CYP enzymes in vitro. A physiologically based pharmacokinetic (PBPK) model was established to evaluate the changes in the ruxolitinib systemic exposures with co-administration of CYP3A4 and CYP2C9 perpetrators. The fractions metabolized in the liver via oxidation by CYP enzymes (fm,CYP3A4 = 0.75, fm,CYP2C9 = 0.19, and fm,CYPothers = 0.06) for an initial ruxolitinib model based on in vitro data were optimized (0.43, 0.56, and 0.01, respectively) using the observed exposure changes of ruxolitinib (10 mg) with co-administered ketoconazole (200 mg). The reduced amount of fm,CYP3A4 was distributed to fm,CYP2C9. For the initial ruxolitinib model with co-administration of ketoconazole, the area under the curve (AUC) increase of 2.60-fold was over-estimated compared with the respective observation (1.91-fold). With the optimized fm values, the predicted AUC ratio was 1.82. The estimated AUC ratios of ruxolitinib by co-administration of the moderate CYP3A4 inhibitor erythromycin (500 mg) and the strong CYP3A4 inducer rifampicin (600 mg) were within a 20% error compared with the clinically observed values. The PBPK modeling results may provide information on the labeling, i.e. supporting a dose reduction by half for co-administration of strong CYP3A4 inhibitors. Furthermore, an AUC increase of ruxolitinib in the absence or presence of the dual CYP3A4 and CYP2C9 inhibitor fluconazole (100–400 mg) was prospectively estimated to be 1.94- to 4.31-fold. Fluconazole simulation results were used as a basis for ruxolitinib dose adjustment when co-administering perpetrator drugs. A ruxolitinib PBPK model with optimized fm,CYP3A4 and fm,CYP2C9 was established to evaluate victim DDI risks. The previous minimal PBPK model was supported by the FDA for the dose reduction strategy, halving the dose with the concomitant use of strong CYP3A4 inhibitors and dual inhibitors on CYP2C9 and CYP3A4, such as fluconazole at ≤200 mg. Fluconazole simulation results were used as supportive evidence in discussions with the FDA and EMA about ruxolitinib dose adjustment when co-administering perpetrator drugs. Thus, this study demonstrated that PBPK modeling can support characterizing DDI liabilities to inform the drug label and might help reduce the number of clinical DDI studies by simulations of untested scenarios, when a robust PBPK model is established.

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A Physiologically Based Pharmacokinetic Model of Parathion Based on Chemical-Specific Parameters Determined In Vitro

Journal of the American College of Toxicology ◽

10.3109/10915819009078766 ◽

1990 ◽

Vol 9 (6) ◽

pp. 611-619 ◽

Cited By ~ 13

Author(s):

Lester G. Sultatos

Keyword(s):

Pbpk Model ◽

Equilibrium Dialysis ◽

Distribution Coefficients ◽

Kinetic Constants ◽

Pbpk Modeling ◽

Pbpk Models ◽

Physiologically Based Pharmacokinetic ◽

Hepatic Extraction Ratio ◽

Physiologically Based

Physiologically based pharmacokinetic (PBPK) modeling is an approach that has been used to predict successfully the pharmacokinetic disposition of numerous foreign chemicals. The accuracy of a PBPK model is dependent on the reliability of estimates of tissue/blood distribution coefficients (Kp) and appropriate kinetic constants descriptive of the elimination of the chemical under consideration. The present study evaluates the validity of the use of Kp values and kinetic constants determined in vitro for use in a PBPK model for the organothiophosphorus insecticide parathion. Kps were determined by equilibrium dialysis, whereas Vmaxs and Kms descriptive of the biotransformation of parathion were calculated from values determined previously in this laboratory. Using these kinetic constants to calculate a hepatic extraction ratio of parathion in the mouse yielded a value identical to that observed with mouse liver perfusions in situ performed previously in this laboratory. Use of Kp values and kinetic constants determined in vitro in a PBPK model accurately simulated levels of parathion in brain, lungs, blood, and liver up to 3 h after intravenous administration of this insecticide. This study demonstrates that chemical-specific parameters determined entirely in vitro can be used to construct accurate PBPK models.

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A Physiologically-Based Pharmacokinetic Framework for Prediction of Drug Exposure in Malnourished Children

Pharmaceutics ◽

10.3390/pharmaceutics13020204 ◽

2021 ◽

Vol 13 (2) ◽

pp. 204

Author(s):

Erik Sjögren ◽

Joel Tarning ◽

Karen I. Barnes ◽

E. Niclas Jonsson

Keyword(s):

Body Composition ◽

Drug Exposure ◽

Drug Disposition ◽

Pediatric Population ◽

Model Performance ◽

Vulnerable Population ◽

Pbpk Modeling ◽

Malnourished Children ◽

Physiologically Based Pharmacokinetic ◽

Physiologically Based

Malnutrition in children is a global health problem, particularly in developing countries. The effects of an insufficient supply of nutrients on body composition and physiological functions may have implications for drug disposition and ultimately affect the clinical outcome in this vulnerable population. Physiologically-based pharmacokinetic (PBPK) modeling can be used to predict the effect of malnutrition as it links physiological changes to pharmacokinetic (PK) consequences. However, the absence of detailed information on body composition and the limited availability of controlled clinical trials in malnourished children complicates the establishment and evaluation of a generic PBPK model in this population. In this manuscript we describe the creation of physiologically-based bridge to a malnourished pediatric population, by combining information on (a) the differences in body composition between healthy and malnourished adults and (b) the differences in physiology between healthy adults and children. Model performance was confirmed using clinical reference data. This study presents a physiologically-based translational framework for prediction of drug disposition in malnourished children. The model is readily applicable for dose recommendation strategies to address the urgent medicinal needs of this vulnerable population.

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Development of a Physiologically Based Pharmacokinetic Model for Hydroxychloroquine and Its Application in Dose Optimization in Specific COVID-19 Patients

Frontiers in Pharmacology ◽

10.3389/fphar.2020.585021 ◽

2021 ◽

Vol 11 ◽

Author(s):

Miao Zhang ◽

Xueting Yao ◽

Zhe Hou ◽

Xuan Guo ◽

Siqi Tu ◽

...

Keyword(s):

Pbpk Model ◽

Clinical Findings ◽

Lung Model ◽

Elderly Subjects ◽

Distribution Data ◽

Physiologically Based Pharmacokinetic ◽

Physiologically Based ◽

Drug Actions

In Feb 2020, we developed a physiologically-based pharmacokinetic (PBPK) model of hydroxychloroquine (HCQ) and integrated in vitro anti-viral effect to support dosing design of HCQ in the treatment of COVID-19 patients in China. This, along with emerging research and clinical findings, supported broader uptake of HCQ as a potential treatment for COVID-19 globally at the beginning of the pandemics. Therefore, many COVID-19 patients have been or will be exposed to HCQ, including specific populations with underlying intrinsic and/or extrinsic characteristics that may affect the disposition and drug actions of HCQ. It is critical to update our PBPK model of HCQ with adequate drug absorption and disposition mechanisms to support optimal dosing of HCQ in these specific populations. We conducted relevant in vitro and in vivo experiments to support HCQ PBPK model update. Different aspects of this model are validated using PK study from 11 published references. With parameterization informed by results from monkeys, a permeability-limited lung model is employed to describe HCQ distribution in the lung tissues. The updated model is applied to optimize HCQ dosing regimens for specific populations, including those taking concomitant medications. In order to meet predefined HCQ exposure target, HCQ dose may need to be reduced in young children, elderly subjects with organ impairment and/or coadministration with a strong CYP2C8/CYP2D6/CYP3A4 inhibitor, and be increased in pregnant women. The updated HCQ PBPK model informed by new metabolism and distribution data can be used to effectively support dosing recommendations for clinical trials in specific COVID-19 patients and treatment of patients with malaria or autoimmune diseases.

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